The data about consumer search behavior from comparison shopping have the highest validity for predicting eventual consumer shopping behavior. It is available even before real-time sales actually happen, have high correlation with actual POS selling data and it is as deep as the SKU level.
“Brand Performance Insights” is the solution developed by CENEJE, in collaboration with EW-Shopp, that will help shoppers (Shopper’s Insights), sellers (Seller’s Insights) and vendors (Vendor’s Insights) to use short term product search insights and behaviour predictions to support their smart purchase or bussiness descisions. The tool is built on top of years of user’s uniquely integrated behavior data of searching products, different category relevant business type of events.
- Shoppers will be able to use relevant purchase information and real time predictions to support their purchase decisions.
- Sellers will manage better pricing, category and campaign management.
- Vendors will get brand and SKU level purchase information in the shortest possible time to react and improve pricing, sales and campaign efficiency.
The impact will be holistic on all market players Shoppers, Vendors and Merchants.
- Shoppers will use the widget to get more info about the searched products and consequently make more informed purchase decisions and gain trust.
- Vendors will gain access to unique almost a real time insights about the purchase behavior and demand predictions for particular category or brand.
- Merchants will get better understanding in category and SKU related sales dynamics through tracking analytics and forecasts based sales/product events and relevant forecasted weather.
- Brand performance Insights will support better tactical business decision such as optimal sales promotion, marketing investment, category and product management, pricing.
- Brand Manufacturers / Distributors
WATCH THE VIDEO: Brand Performance Insights: predicting shopper interaction with advanced data management
RESEARCH & INNOVATION DOMAIN: Data integration, data aggregation, modeling, predictions, web design
TOOLS INVOLVED: Qminer, MariaDb, MsSql
CONTACT PERSON: Darko Dujic email@example.com